Container Berths Optimal Allocation Of Resources

With the growth of global economy and the development of international shipping market, the quantity of cargo transported by containership increases quickly and the containership also becomes more and more bigger. The increase of container quantity and the need of container port high-level service force the port managers to take all kinds of measures, one of which is optimizing the berth resource in existence. Namely, they allocate reasonable berth and choose appropriate anchor order for the vessels on arrival to minimize the total cost of all the vessels at port in some time and advance the efficiency of port., so attract more vessels to anchor.Based on the analysis of the different factors of berth allocation in container port, we studied the optimization methods of berth allocation deeply and formulated the mathematics model of the berth allocation, whose objective is to minimize the sum of costs of the ships stayed in the ports. According to the characteristic of the module, the physical significance of the parameters and correlation each other, we lead to the constraint qualifications of the berth allocation. The model based on minimization cost is more accorded with the actual condition of berth allocation. The importances of ships in port are fully considered in this model. In general, the unit time cost of big ship is higher and that of small ship is lower, so the big ship should be berthed as soon as possible to minimize the sum of costs of the ships stayed in the ports.In order to realize the berth allocation rationalization, we should find the best berth allocation plan in all the possible plans. Therefore we use an genetic algorithm based on integer coding to solve the problem and write the corresponding programme in C++ language to realize it. The genetic algorithm (GA) is a new optimization method produced recently years, and it is a kind of random searching method that simulated natural selection and evolution based on the numbers of genus groups. Compared with the general optimization method, GA has two notable characters, one character is latent parallel and the other is searching in the whole area, so it easy to find the best one in whole area not in local area. The characters of GA decide it operated in all the possible results and keep a higher choose pressure in evolution, and the fitness of solution searched more and more higher, and find the best solution at last. In the end, we validate the feasibility of this mathematics model to be used in solving the berth allocation problem by a calculate example.